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WaveSpeed AI Video Upscaler

wavespeed-ai /

AI Video Upscaler enhances resolution and clarity to fix blurry Sora 2 output and improve low-resolution footage with ML upscaling. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

upscaler
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$0.025cho mỗi 5 giây độ dài video·~40 / $1

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README

Video Upscaler

Upscale videos to 720p, 1080p, 2K, or 4K with a simple upload. Optimized for clarity, detail fidelity, and flicker-free temporal consistency — all with faster turnaround times. No local setup required.

Looking for the absolute best quality? Try our Ultimate Video Upscaler, Video Upscaler Pro, or FlashVSR for maximum detail and fidelity.

Why it looks great

  • Temporal consistency: minimizes flicker and ghosting across frames for stable motion.
  • Detail reconstruction: restores fine textures (hair, fabric, foliage) and sharp edges without over-sharpening.
  • Artifact cleanup: reduces compression blocks, ringing, and shimmering in challenging shots.
  • Motion-aware upscaling: preserves fast action and camera pans with fewer motion artifacts.
  • Natural look: balances perceptual quality with crispness to avoid plastic or overprocessed outputs.

Limits and Performance

  • Max clip length per job: up to 10 minutes
  • Processing speed: approximately 5–10 seconds of wall time to process 1 second of video (varies by resolution and queue load)

Pricing

Per-second billing with a 5-second minimum. The table below lists prices per 5 seconds for easy comparison.

Output ResolutionCost per 5 seconds
720p$0.025
1080p$0.025
2K$0.05
4K$0.10

Billing Rules

  • Minimum charge: 5 seconds
  • Per-second rate = (price per 5 seconds) ÷ 5
  • Billed duration = video length in seconds (rounded up), with a 5-second minimum
  • Total cost = billed duration × per-second rate (by output resolution)

Examples

  • 3.2s @ 1080p → billed as 5s minimum → 5 × $0.005 = $0.025
  • 12s @ 1080p → 12 × $0.005 = $0.06
  • 23s @ 2K → per-second $0.01 → 23 × $0.01 = $0.23
  • 2m01s (121s) @ 4K → per-second $0.02 → 121 × $0.02 = $2.42

How to Use

  1. Choose the target resolution and parameters.
  2. Upload your video (≤ 10 minutes).
  3. Submit the job and wait for processing.
  4. Preview and download the result.

Pro tips for best quality

  • Upload the highest-quality source you have; avoid heavily compressed inputs when possible.
  • Keep original frame rate; avoid unnecessary re-encoding before upload.
  • Pick the lowest resolution that meets your delivery needs (1080p = speed/cost, 2K/4K = maximum detail).
  • For long videos, process in segments to parallelize and then merge.

Notes

  • Actual processing time may vary based on resolution, model choice, and current queue.
  • For videos longer than 10 minutes, split into multiple segments, process separately, and merge afterward.
Lưu ý:Trang web này sử dụng các mô hình AI do bên thứ ba cung cấp.

Video Upscaler API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/video-upscaler with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Video Upscaler below.

HTTP example
set -euo pipefail

: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"

REQUEST_BODY=$(cat <<'JSON'
{
    "video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4",
    "target_resolution": "1080p"
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/video-upscaler" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d "$REQUEST_BODY")

TASK=$(printf '%s' "$SUBMIT_RESPONSE" | jq 'if has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "$TASK" | jq -r '.id')
if [ -z "$PREDICTION_ID" ] || [ "$PREDICTION_ID" = "null" ]; then
  printf 'Submission response did not contain a prediction id
' >&2
  exit 1
fi
RESULT_URL=$(printf '%s' "$TASK" | jq -r '.urls.get // empty')
if [ -z "$RESULT_URL" ]; then
  RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"
fi

# 2. Poll until the prediction finishes.
while true; do
  RESPONSE=$(curl --silent --show-error --fail-with-body "$RESULT_URL" \
    -H "Authorization: Bearer $WAVESPEED_API_KEY")
  RESULT=$(printf '%s' "$RESPONSE" | jq 'if has("data") then .data else . end')
  STATUS=$(printf '%s' "$RESULT" | jq -r '.status')
  case "$STATUS" in
    completed) printf '%s\n' "$RESULT" | jq '.outputs'; break ;;
    failed|cancelled|timeout) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
    created|processing) sleep 2 ;;
    *) printf 'Unexpected status: %s
' "$STATUS" >&2; exit 1 ;;
  esac
done
Node.js example
const submitUrl = "https://api.wavespeed.ai/api/v3/wavespeed-ai/video-upscaler";
const apiKey = process.env.WAVESPEED_API_KEY;
if (!apiKey) throw new Error('Set WAVESPEED_API_KEY');

async function requestJson(url, options = {}) {
  const response = await fetch(url, options);
  if (!response.ok) throw new Error(await response.text());
  return response.json();
}

// 1. Submit the prediction.
const body = await requestJson(submitUrl, {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4",
        "target_resolution": "1080p"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${task.id}/result`;

// 2. Poll until the prediction finishes.
while (true) {
  const resultBody = await requestJson(resultUrl, {
    headers: { "Authorization": `Bearer ${apiKey}` },
  });
  const result = resultBody.data ?? resultBody;
  if (result.status === "completed") {
    console.log(result.outputs);
    break;
  }
  if (["failed", "cancelled", "timeout"].includes(result.status)) throw new Error(JSON.stringify(result));
  if (!["created", "processing"].includes(result.status)) throw new Error("Unexpected status: " + result.status);
  await new Promise(resolve => setTimeout(resolve, 2000));
}
Python example
import json
import os
import time
from urllib.request import Request, urlopen

api_key = os.environ["WAVESPEED_API_KEY"]
headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
payload = {
    "video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4",
    "target_resolution": "1080p"
}

def request_json(url, data=None):
    request = Request(url, data=data, headers=headers, method="POST" if data else "GET")
    with urlopen(request) as response:
        return json.load(response)

# 1. Submit the prediction.
body = request_json("https://api.wavespeed.ai/api/v3/wavespeed-ai/video-upscaler", json.dumps(payload).encode())
task = body.get("data", body)
if not task.get("id"):
    raise RuntimeError("Submission response did not contain a prediction id")
result_url = task.get("urls", {}).get("get") or f"https://api.wavespeed.ai/api/v3/predictions/{task['id']}/result"

# 2. Poll until the prediction finishes.
while True:
    result_body = request_json(result_url)
    result = result_body.get("data", result_body)
    status = result.get("status")
    if status == "completed":
        print(result.get("outputs", []))
        break
    if status in {"failed", "cancelled", "timeout"}:
        raise RuntimeError(result)
    if status not in {"created", "processing"}:
        raise RuntimeError(f"Unexpected status: {status}")
    time.sleep(2)

Video Upscaler API — Frequently asked questions

What is the Video Upscaler API?

Video Upscaler is a WaveSpeedAI model for upscaling, exposed as a REST API on WaveSpeedAI. AI Video Upscaler enhances resolution and clarity to fix blurry Sora 2 output and improve low-resolution footage with ML upscaling. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the Video Upscaler API?

POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID. Poll the result endpoint starting around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. The playground generates production-oriented Python, JavaScript, and cURL examples with timeouts, transient-error handling, and safe GET retries. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/wavespeed-ai/video-upscaler.

How much does Video Upscaler cost per run?

Video Upscaler starts at $0.025 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.

What inputs does Video Upscaler accept?

Key inputs: `video`, `target_resolution`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/wavespeed-ai/video-upscaler.

How long does Video Upscaler take to generate?

Median end-to-end generation time on WaveSpeedAI is around 39 seconds per request, based on recent successful runs. Queue time varies with global demand; live status is visible in the prediction record.

Can I use Video Upscaler outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (WaveSpeedAI). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.

WaveSpeed AI Video Upscaler | AI Video Upscaler API | WaveSpeedAI